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The Origins and Consequences of Affective Polarizationin the United States
Shanto Iyengar1, Yphtach Lelkes2, Matthew Levendusky3, Neil Malhotra4,and Sean J. Westwood5
1Department of Political Science, Stanford University2Annenberg School of Communication, University of Pennsylvania
3Department of Political Science, University of Pennsylvania4Graduate School of Business, Stanford University5Department of Government, Dartmouth College
April 23, 2018
Word count: 7,970
Citation count: 100
America, we are told, is a divided nation. What does this mean? Political elites—
particularly members of Congress—increasingly disagree on policy issues (McCarty, Poole,
and Rosenthal, 2006), though there is still an active debate about whether the same is true
of the mass public (Abramowitz and Saunders, 2008; Fiorina, Abrams, and Pope, 2008).
But regardless of how divided Americans may be on the issues, a new type of division has
emerged in the mass public in recent years: ordinary Americans increasingly dislike and
distrust those from the other party.
Democrats and Republicans both say that the other party’s members are hypocritical,
selfish, and closed-minded, and they are unwilling to socialize across party lines, or even
to partner with opponents in a variety of other activities. This phenomenon of animosity
between the parties is known as affective polarization. We trace the origins of affective
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polarization to the power of partisanship as a social identity, and explain the variety of factors
that intensify partisan animus. We also explore the consequences of affective polarization,
highlighting how partisan affect influences attitudes and behaviors well outside the political
sphere. Finally, we discuss strategies that might mitigate partisan discord, and conclude
with some suggestions for future work.
Affective Polarization: an Outgrowth of Partisan Social
Identity
Homo sapiens is a social species; group affiliation is essential to our sense of self. Indi-
viduals instinctively think of themselves as representing broad socio-economic and cultural
categories rather than as distinctive packages of traits (Brewer, 1991; Tajfel, 1978). Among
these categories, political parties subsist precisely because group identities are so stable and
significant (Lipset and Rokkan, 1967).
In the U.S., partisanship is about identifying with the “Democrat” group or the “Re-
publican” group (Green, Palmquist, and Schickler, 2002; Huddy, Mason, and Aarøe, 2015).
A host of behavioral consequences flow from that identification. When we identify with a
political party, we instinctively divide up the world into an in group (our own party), and
an out group (the opposing party; see Tajfel and Turner 1979). A vast literature in social
psychology demonstrates that any such in-group/out-group distinction, even one based on
the most trivial of shared characteristics, triggers both positive feelings for the in group, and
negative evaluations of the out group (see, e.g., Billig and Tajfel, 1973). The more salient
the group to the sense of personal identity, the stronger these inter-group divisions (Gaertner
et al., 1993).
Partisanship is a particularly salient and powerful identify for several reasons. First, it is
acquired at a young age, and rarely changes over the life-cycle, notwithstanding significant
shifts in personal circumstances (Sears, 1975). Second, political campaigns—the formal
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occasions for expressing ones partisan identity—recur frequently, and last for many months
(or even years) in the contemporary U.S. Indeed, some even argue that modern governance is
effectively always about the next campaign (Lee, 2016), meaning that individuals constantly
receive partisan cues from elites. It is no surprise, therefore, that ordinary Americans see
the political world through a partisan prism.
From a social identity perspective, affective polarization is a natural offshoot of this sense
of partisan group identity: “the tendency of people identifying as Republicans or Democrats
to view opposing partisans negatively and copartisans positively” (Iyengar and Westwood,
2015, 691). However, changes in the contemporary political and media environment have
further exacerbated the divide in recent years, as we explain below.
Our conceptualization of polarization as rooted in affect and identity stands in contrast
to a long tradition in political science of studying polarization as the difference between the
policy positions of Democrats and Republicans (Fiorina, Abrams, and Pope, 2005). Indeed,
there is ongoing scholarly disagreement over the extent of such ideological polarization.
Some scholars argue that the mass public has polarized on the issues, citing a decline in
the number of ideological moderates and a near doubling of the average distance between
the ideological self-placement of non-activist Democrats and Republicans between 1972 and
2004 (Abramowitz and Saunders, 2008). Others dispute this description of the masses,
maintaining that the median citizen remains a centrist rather than an extremist on most
issues (Fiorina, Abrams, and Pope, 2008).
We do not take a position on this ongoing debate. Rather, we argue that affective polar-
ization is largely distinct from the ideological divide, and that extremity in issue opinions is
not a necessary condition for affective polarization (Iyengar, Sood, and Lelkes, 2012; Mason,
2015). Indeed, in some settings, affective polarization can increase while ideological divisions
shrink (Levendusky and Malhotra, 2016a). While there are important connections between
affective and ideological polarization that we return to below (Abramowitz and Webster,
2016), they are theoretically and empirically distinct concepts. Here, we focus exclusively
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on the affective dimension of polarization.
How Do We Measure Affective Polarization?
Scholars have used three main classes of techniques to measure affective polarization: survey
self-reports of partisan affect, implicit or sub-conscious tests of partisan bias, and behavioral
measures of inter-personal trust and group favoritism or discrimination based on partisan
cues.
Survey Self-Reports
Survey self-reports are the most basic and widely used measure of affective polarization in the
literature. While scholars have relied on a number of different survey items, the most central
is the “feeling thermometer” question from the American National Election Study (ANES)
time series. The feeling thermometer was originally created as a “neutrally worded means
of eliciting responses to a wide variety of candidates” (Weisberg and Rusk, 1970, 1168), but
has become the primary vehicle for measuring affect toward a wide range of groups in the
electorate. Typically respondents are asked to rate “Democrats” and “Republicans” (or the
Democratic and Republican Parties) on a 101-point scale ranging from cold (0) to warm
(100). Affective polarization is then computed as the difference between the score given to
the party of the respondent and the score given to the opposing party. In the ANES time
series (see Figure 1), this measure shows a significant increase in affective polarization in the
period after 1980, rising from 22.64 degrees in 1978 to 40.87 degrees in 2016 (Westwood and
Lelkes, 2018; Iyengar, Sood, and Lelkes, 2012). It is particularly noteworthy that 1) it is not
so much that people like their own party more over time; rather, there is an increase in out-
party animus, especially in recent years and 2) that affective polarization actually decreased
between 2012 and 2016. Other over-time measures of partisan affect—for example, those
from the Pew Research Center—show similar patterns (Pew Research Center, 2017).
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Figure 1: Partisan Feeling and Affective Polarization Overtime (ANES)
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Affective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective PolarizationAffective Polarization
Out−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feelingOut−group feeling
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1980 1990 2000 2010
Year
While the feeling thermometer is the workhorse survey item, scholars have also adopted
a variety of alternative measures. For instance, Levendusky (2018) and Levendusky and
Malhotra (2016a) use trait ratings of party supporters to measure affective discord: are they
intelligent, open-minded, and generous, or hypocritical, selfish, and mean (see also Garrett
et al., 2014; Iyengar, Sood, and Lelkes, 2012)? Levendusky and Malhotra (2016a) also use
the number of likes and dislikes of the parties people can bring to mind as a quasi-behavioral
measure. Other scholars have substituted the extent to which the presidential candidates
elicit either positive or negative emotional responses as the metric for assessing affective
polarization (Lelkes, Sood, and Iyengar, 2017).
A more unobtrusive measure of partisan affect is social distance, the extent to which
individuals feel comfortable interacting with out-group members in a variety of different
settings. If partisnaship is an important social identity in its own right, partisans should be
averse to entering into close inter-personal relations with their opponents. Iyengar, Sood,
and Lelkes (2012) show that Americans have become increasingly averse to the prospect
of their child marrying someone from the opposing party. In 1960, only 4-5% were upset
with their child marrying someone from the out party, but that figure had jumped to one-
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third of Democrats and one-half of Republicans by 2010 (416-8). However, Klar, Krupnikov,
and Ryan (Forthcoming) show that social distance measures conflate partisan animus and
a dislike of politics: when people are asked about their child marrying someone from the
opposing party, they assume that partisanship is a salient part of that person’s identity.
When respondents were told prior to the question that the potential spouse in question is
largely apolitical, their opposition falls sharply. Similarly, their opposition rises to same-
party marriage when they are told the person frequently discusses politics. This suggests
that part of the opposition to inter-party marriage (and other types of social distance)
may be that people assume “Republicans” and “Democrats” are the extremists portrayed
in the media (Levendusky and Malhotra, 2016a), rather than their more typical apolitical
brethren. Alternatively, the finding may reflect the well-known association between politics
and disagreement; most people prefer to be in agreeable relationships. Understanding the
precise limitations of social distance measures is an important topic for future research.
Implicit Measures
A major limitation to survey-based indicators of partisan affect is that they are reactive and
susceptible to intentional exaggeration/suppression based on normative pressures. Unlike
race, gender, and other social divides where group-related attitudes and behaviors are sub-
ject to social norms (Maccoby and Maccoby, 1954), there are no corresponding pressures
to temper disapproval of political opponents. If anything, the rhetoric and actions of po-
litical leaders demonstrate that hostility directed at the opposition is acceptable and often
appropriate. Implicit measures are known to be much harder to manipulate than explicit
self-reports; they are therefore more valid and less susceptible to impression management
(Boysen, Vogel, and Madon, 2006).
Iyengar and Westwood (2015) developed an Implicit Association Test (based on the brief
version of the race IAT) to document unconscious partisan bias. Their results showed that
implicit bias is ingrained with approximately 70% of Democrats and Republicans showing a
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bias in favor of their party. Interestingly, implicit bias is less pronounced than explicit bias
as measured through survey questions; 91% of Republicans and 75% of Democrats in the
same study explicitly evaluated their party more favorably.
To place the results from their party IAT in context Iyengar and Westwood also adminis-
tered the race IAT. Relative to implicit racial bias, implicit partisan bias is more widespread.
The difference in the D-score—the operational indicator of implicit bias—across the party
divide was .50, while the corresponding difference in implicit racial bias across the racial
divide was only .18 (see also Theodoridis (2017) for an application of implicit measures to
the study of partisanship). 1
Behavioral Measures
Of course, one can also critique measures of implicit attitudes, especially on the grounds
that they are weak predictors of relevant behaviors. Given the limits of the attitudinal
approach, scholars have turned to behavioral manifestations of partisan animus in both
lab and naturalistic settings. Iyengar and Westwood (2015) and Carlin and Love (2013)
introduce economic games as a platform for documenting the extent to which partisans are
willing to endow or withhold financial rewards from players who either share or do not
share their partisan affiliation. Using both the trust game and the dictator game, this
work measures partisan bias as the difference between financial allocations to co-partisans
and opposing partisans. Results show that co-partisans consistently receive a bonus while
opposing partisans are subject to a financial penalty.
Iyengar and Westwood (2015) further document the extent of affective polarization by
comparing the effects of partisan and racial cues in non-political settings. In one study, they
asked participants to select one of two candidates for a college scholarship. The candidates—
both high school students—had similar academic credentials, but differed in their ethnicity
(White or African American) or partisanship (Democrat or Republican). The results indi-
1Ryan (2017) shows that when explicit political preferences are weak these underlying implicit preferencesdrive political decision-making.
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cated little racial bias; Whites, in fact, preferred the African American applicant (55.8%).
79.2% of Democrats picked the Democratic applicant and 80% of Republicans picked the
Republican applicant. These results held even when the out-partisan candidate had a sig-
nificantly higher GPA (4.0 v. 3.5); the probability of a partisan selecting the more qualified
out-party candidate was never above 30%.
The scholarship study showed that partisan cues exert strong leverage over non-political
attitudes. This phenomenon of affective spillover has been documented in a variety of do-
mains including evaluations of job applicants (Gift and Gift, 2015), dating behavior (Huber
and Malhotra, 2017), and online labor markets (McConnell et al., 2018). This work con-
sistently shows that partisanship has bled into the non-political sphere, driving ordinary
citizens to reward co-partisans and penalize opposing partisans, a point to which we return
below.
Regardless of measurement technique, the literature consistently documents an affective
and behavioral divide between the in-party and the out-party. Further measurement exercises
show that while affective polarization predicts both political and private behavior, it has yet
to rise to the level of overt discrimination as conceptualized in social psychology (Lelkes and
Westwood, 2017). Understanding the limits to affective polarization, and what constrains
these sentiments, therefore, is another important realm for future study.
Origins and Causes of Affective Polarization
A number of features of the contemporary environment have exacerbated partisans’ procliv-
ity to divide the world into a liked in group (one’s own party) and a disliked out group (the
opposing party). First, in the last 50 years, the percentage of “sorted” partisans, i.e., parti-
sans who identify with the party most closely reflecting their ideology, has steadily increased
(Levendusky, 2009). When most Democrats [Republicans] are also liberals [conservatives],
they are less likely to encounter conflicting political ideas and identities (Roccas and Brewer,
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2002), and are more likely see non-identifiers as socially distant. Sorting likely leads people to
perceive both opposing partisans and co-partisans as more extreme than they really are, with
misperceptions being more acute for opposing partisans (Levendusky and Malhotra, 2016b).
As partisan and ideological identities became increasingly aligned, other salient social iden-
tities, including race and religion, also converged with partisanship. White evangelicals,
for instance, are overwhelmingly Republican today, and African-Americans overwhelmingly
identify as Democrats. This decline of cross-cutting identities is at the root of affective
polarization according to Mason (2015, 2018b). She has shown that those with consistent
partisan and ideological identities became more hostile towards the out-party without nec-
essarily changing their ideological positions, and those that have aligned religious, racial,
and partisan identities react more emotionally to information that threatens their partisan
identities or issue stances. In essence, sorting has made it much easier for partisans to make
generalized inferences about the opposing side, even if those inferences are inaccurate.
While reinforcing social identities seem to be a key factor explaining affective polarization,
other work finds that ideological polarization also impacts affective polarization (Rogowski
and Sutherland, 2016; Bougher, 2017). Observational time-series and panel data indicate
that increasing ideological extremity and constraint are both associated with stronger par-
tisan affect (Bougher, 2017), and experimental work that manipulates the degree to which
a candidate is “liberal” or “conservative” also impacts affective polarization (Rogowski and
Sutherland, 2016; Webster and Abramowitz, 2017).
The high-choice media environment and the proliferation of partisan outlets are frequently
blamed for the current polarized environment (e.g., Lelkes, Sood, and Iyengar, 2017). The ar-
gument goes that partisan news activates partisan identities and subsequent feelings towards
the political parties. One feature of any social identity is that, in order to fit in with the
group, identifiers must adopt the attitudes of prototypical in-group members (Hogg, 2001).
Partisan outlets—many of which depict the opposing party in harsh terms, often comparing
out-partisans to Nazis and Communists (Berry and Sobieraj, 2014), and by focusing dis-
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proportionately on out-party scandals (real or imagined)—inculcate hostility toward the out
group (Puglisi and Snyder, 2011).
Further, the lack of balanced content in these outlets may persuade viewers to adopt
extreme ideological positions (Levendusky, 2013), which, in turn, increases affective polar-
ization (Rogowski and Sutherland, 2016; Webster and Abramowitz, 2017). While both survey
and experimental research supports this hypothesis (Stroud, 2010; Levendusky, 2013), the
precise mechanism is unclear because the treatment is typically exposure to an outlet or
cable news show, making it difficult to tease apart the effects of exposure to extreme policy
positions, the priming of partisanship, or the cultivation of hostility toward the other side.
It is far from clear, however, that partisan news actually causes affective polarization.
First, those who are the most polarized are, of course, more motivated to watch partisan
news (Arceneaux and Johnson, 2013). Arguably, therefore, partisan news has little impact
on polarization. Levendusky (2013), however, finds that exposure to partisan news makes
those with extreme attitudes even more extreme. While these studies focus on ideological
polarization, the ability to opt out of exposure to partisan news may also further weaken the
impact of partisan media on affective polarization.
Another mitigating factor is that partisans may not have a clear preference for ideologi-
cally or identity-consistent information. While some studies have found evidence of selective
exposure to partisan information (e.g., Stroud, 2011), others find that Americans typically
select ideologically neutral content (e.g., Gentzkow and Shapiro, 2011). So even if partisan
news or other identity-consistent information heightens affective polarization, few people
may actually limit their exposure to sources representing a particular identity or ideology
(see also Bakshy, Messing, and Adamic, 2015).
The relationship between Internet access, a major route to partisan media, and affective
polarization is similarly contested. Using state Right-of-Way laws as an instrument for
Internet access, Lelkes, Sood, and Iyengar (2017) find a positive small, relationship between
Internet access and affective polarization. On the other hand, Boxell, Gentzkow, and Shapiro
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(2017) find that affective polarization has increased the most among those least likely to use
social media and the Internet. Given these inconsistent results, it is too early to conclude
that Internet usage (and the availability of a wider array of information) plays a definite role
in the growth of affective polarization.
While the high-choice media environment of cable and the Internet allow those uninter-
ested in politics to “check out,” exposure to partisan news can occur in other ways. First,
as people spend more time online and on social network sites, they are more likely to be
inadvertently exposed to polarizing content by others in their network (Bakshy, Messing,
and Adamic, 2015). Additionally, people may be exposed to partisan news content indi-
rectly through discussion with peers. Druckman, Levendusky, and McLain (2018) randomly
assigned subjects to watch partisan media, and, later participate in discussions with those
who did not watch the stimuli. Those in groups that contained people who watched the
stimuli were significantly more (ideologically) polarized than those who were not in such
groups. This result suggests that partisan media—and other related outlets—may play a
more significant role than initially thought because their messages can be amplified by social
networks and two-step communication flows.
Partisan commentary is not the only type of media content that can polarize Americans.
First, the mainstream media has increasingly focused on polarization. According to one
content analysis, there are roughly 20 percent more stories about polarization in America
today than there were at the turn of the 21st century (Levendusky and Malhotra, 2016a).
Experimental evidence suggests that coverage of polarization increases affective polarization
but decreases ideological polarization (Levendusky and Malhotra, 2016a).
Political campaigns also exacerbate partisan tensions (Sood and Iyengar 2016). Across
recent election cycles, people were between 50 percent and 150 percent more affectively po-
larized by election day than they were a year earlier. Additionally, by identifying people who
live in the designated market area of a neighboring battleground state, Sood and Iyengar
(2016) show that political advertisements, and especially negative advertising, have partic-
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ularly strong effects on affective polarization (see also Iyengar, Sood, and Lelkes, 2012).
Political campaigns may heighten tensions in a number of ways. For instance, campaigns
make partisanship more salient (Michelitch and Utych, Forthcoming), and regularly run ads
that portray the other side as an existential threat.
Finally, increasingly homogeneous online and offline interpersonal networks may be con-
tributing to affective polarization. As partisans become more isolated from each other (Gim-
pel and Hui, 2015) in their real and virtual lives, they are more likely to encounter only
like-minded voices, further exacerbating polarization. While provocative, and certainly part
of the popular discourse, the scholarly evidence on social homophily is mixed. For one thing,
there is little evidence that people are increasingly living in partisan enclaves (Mummolo
and Nall, 2017). However, it is clear that families have become more politically homoge-
neous. Spousal agreement on party affiliation now exceeds 80 percent, with parent-offspring
agreement at 75 percent, both figures representing large increases in family agreement since
the 1960s (Iyengar, Konitzer, and Tedin, 2017). In the case of online behavior, as we noted
earlier, the first analysis of partisan segregation in the audience for online news (Gentzkow
and Shapiro, 2011) showed that most Americans encountered diverse points of view. More
recent work, however, suggests that the polarization of online news audiences has increased,
especially when considering exposure to election-related news. All told, therefore, it is pre-
mature to reach any firm conclusions about the role of “echo chambers,” either in-person or
online, as causes of affective polarization.
The Non-Political Consequences of Affective Polariza-
tion
One major concern is that partisan animus might spill over and affect behaviors and attitudes
outside the political realm. It is one thing if partisan disagreements are confined to political
contestation, but quite another if everyday interactions and life choices are compromised by
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politics.
For instance, does partisanship affect the social relations we seek to enter into, whether
it be friendships, romantic relationships, or marriages? Since partisanship increasingly sig-
nals core values and worldview, it is unsurprising that partisanship is used to screen social
partners. People may also perceive copartisans to be more physically attractive (Nicholson
et al., 2016).2 Longitudinal survey data has shown that people self-report that they are less
comfortable with social relationships with out partisans. According to Iyengar, Sood, and
Lelkes (2012), the percentage of Americans who would be somewhat or very unhappy if their
child married someone of the opposite party has increased by about 35 percentage points
over the last 50 years, with Republicans especially sensitive to cross-party marriage. These
increases are much larger in the United States compared to a similar advanced democracy
(the United Kingdom). And these preferences appear substantively larger than apolitical
benchmarks such as the 17%-20% of people who would not want their child marrying a fan
of an opposing baseball team (Hersh, 2016). Behavioral data from smartphone activity con-
firms that Americans are averse to cross-partisan dialogue within their families, especially
in the wake of the 2016 election (Chen and Rohla, 2017).
Although people may state that they do not want to enter to in relationships with people
of the opposing party, does their behavior match their self-reports? Observational survey
data has long found that marriages are much more politically homogenous than one would
expect by chance (Stoker, 1995). This finding has been validated in large voter files, which
show that 80.5% of married couples share a party identification (Iyengar, Konitzer, and Te-
din, 2017), and that selection rather than convergence over time explains spousal agreement.3
Of course, any data collected after people have married is of limited utility for assessing
whether people prefer to engage in romantic relationships with people of the opposing party.
2However, Huber and Malhotra (2017) run similar experiments to Nicholson et al. (2016) including morecontextual information along the lines of a conjoint design and find no effect of shared partisanship onperceived attractiveness.
3Using the Catalyst subsample, Hersh and Ghitza (2017) find somewhat lower spousal agreement (70%),but even here, it is still significantly higher than chance alone would predict.
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This is because homophily can be induced by various factors unrelated to selection: (1)
post-marriage conversion; (2) the influence of shared environment; (3) structural features
of the available partner pool. As a result, some recent research has attempted to use data
from online dating websites to assess whether political homophily in relationships is due to
selection based on political profiles. Huber and Malhotra (2017) leverage data from an online
dating website where they have access to both the profile characteristics of daters as well
as their messaging behavior. They find that partisan matching increases the likelihood of a
dyad exchanging messages by 9.5%. To put that finding into context, analogous figures for
dating pairs matched by level of education and religion are 10.6% and 50.0%, respectively.
On the one hand, these substantive effects might be smaller than survey data would imply.
On the other hand, partisan sorting seems to be on a par with socio-economic status, long
considered the major basis for the selection of long-term partners. Huber and Malhotra
(2017) corroborate this finding with data from a survey experiment where partisanship is
randomly manipulated in the dating profiles.
The findings of Huber and Malhotra (2017) appear to conflict with other data from public
online dating profiles (Klofstad, McDermott, and Hatemi, 2013). Although these studies do
not have access to the messaging behavior going on behind the scenes, they find that online
daters usually do not advertise their political preferences, which would seem inconsistent
with the idea of people actively selecting on this information. However, dating behavior
may be changing. The dating website eHarmony reported that dating profiles typically did
not report political affiliation prior to the 2016 presidential election (24.6% of women and
16.5% of men). After the 2016 presidential election, these figures increased to 68% and 47%,
respectively (Kiefer, 2017), suggesting that in the wake of the divisive 2016 election, a sea
change may be underway.
If the thought of romantic relationships with an opposing partisan is a bridge too far,
one might ask whether people are more tolerant of the relationship as merely friendship.
Survey data from the Pew Research Center suggest this is unlikely to be the case. About
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64% of Democrats and 55% of Republicans say they have “just a few” or “no” close friends
who are from the other political party (Pew Research Center, 2017). Huber and Malhotra
(2017) also find in their survey experiment that discordant partisanship decreases people’s
likelihood to being friends with someone even if they do not want a romantic relationship.
Chopik and Motyl (2016) find that living in a politically incongruent area made it more
difficult for people to form friendships. Behavioral data seem to confirm that people seek
to hide their partisanship from peers when they are living in a politically discordant loca-
tion. Using data on political donations, Perez-Truglia and Cruces (2017) find that people
signal their conformity via donations to opposite-party peers, perhaps out of fear of social
reprisal. Finally, Facebook data show that the median proportion of friendship groups that
are ideologically discordant is only about 20% (Bakshy, Messing, and Adamic, 2015).
If people seek to socialize with people they are likely to agree with politically, it stands
to reason that they may choose to locate themselves near like-minded individuals. Indeed,
survey data suggests that people self-report desiring to move to locations with fellow parti-
sans (Gimpel and Hui, 2015). The idea of residential sorting based on partisanship was first
popularized by Bishop (2009), who reported descriptive statistics showing that counties had
become more politically homogeneous over time. However, Klinkner (2004) challenged much
of this data analysis by showing that residential sorting has not increased significantly over
the past few decades when one analyzes party registration data instead of presidential vote
returns. Further, in contrast to Gimpel and Hui (2015), Mummolo and Nall (2017) show that
revealed preferences concerning place of residence diverge from stated preferences. Although
people claim they would like to move to a more politically compatible area (e.g., Democrats
claiming they would move to Canada following Bush’s 2004 reelection), mobility data sug-
gests that people are not moving for political reasons, largely because other non-political
factors—such as the quality of the public schools—dominate the decisions of Democrats and
Republicans alike.
Thus far, we have mainly explored if partisanship spills over into people’s social interac-
15
tions. But can partisanship also distort economic behavior? Michelitch’s (2015) pioneering
work in this area found that Ghanaian taxi drivers accept lower prices from co-partisans and
demand higher prices from counter-partisans. Specifically, non-coethnic counter-partisans
pay 16% more and non-coethnic co-partisans 6% more in taxi fares than coethnic co-
partisans, suggesting an interaction between both ethnicity and partisanship. McConnell
et al. (2018) conducted a field experiment in the U.S. in which people were provided the op-
portunity to buy a heavily discounted gift card. Some buyers were assigned to conditions in
which they learned that the seller was either a co-partisan or counter-partisan. They found
no evidence of out-group animus; the purchasing rate remained stable across same party
and opposite party sellers. However, interacting with a co-partisan seller nearly doubled
the purchasing price of the gift card. The effects were even larger among strong partisans.
Panagopoulos et al. (2016), on the other hand, find evidence of out-group animus: 15%-
20% of participants in their study were less willing to accept a gift card from a company
that gives PAC donations to the opposing party. While Panagopoulos et al. (2016) observe
larger effect sizes than McConnell et al. (2018), that could be because their study took place
within the less-natural context of a survey experiment. Indeed, in Panagopoulos et al.’s
(2016) replication study done in the field, the effect sizes fell to about 5 percentage points.
In addition to product markets, partisanship can distort labor markets. Using an audit
design, Gift and Gift (2015) mailed out resumes signaling job applicants’ partisan affiliation
in a heavily Democratic area and a heavily Republican area. They find that in the Democratic
county, Democratic resumes were 2.4 percentage points more likely to receive a callback
than Republican resumes; the corresponding partisan preference for Republican resumes in
the Republican county was 5.6 percentage points. Whereas Gift and Gift (2015) examine
employer preferences, McConnell et al. (2018) examine the other side of the labor market and
study how partisanship affects employee behavior. The researchers hired workers to complete
an online editing task and subtly signalled the partisan identification of the employer. Unlike
Gift and Gift (2015), they mainly find evidence of in-group affinity as opposed to out-group
16
prejudice. The only significant differences occurred between the co-partisan condition and
the control group. People exhibited a willingness to accept lower compensation (by 6.5%)
from a partisan congruent employer. At the same time, they performed lower-quality work
and exhibited less effort. Although the mechanism for this performance deficit is unclear,
one possibility is that they perceive the employer to be of higher quality and therefore less
likely to make copy-editing mistakes.
In addition to affecting economic decisions, partisanship colors how people perceive the
state of the economy. A seminal finding in political behavior research is that people tend to
believe that economic outcomes (e.g., GDP growth, unemployment rate) are more favorable
(unfavorable) when their party is in (out of) the White House (Bartels, 2002). These percep-
tual biases seem most pronounced when the actual state of the economy is ambiguous (Healy
and Malhotra, 2013). These findings have recently been challenged on the grounds that sur-
vey responses are expressive cheap talk (Bullock et al., 2015; Prior, Sood, and Khanna,
2015). The partisan gap in economic perceptions narrows—but does not disappear—when
survey respondents are financially incentivized to provide accurate answers about the state
of the economy. Of more course, one concern with these findings is that voting, like the
typical survey response, is an expressive act, not an incentivized one (see also Berinsky,
2018). Moreover, the correlation between vote choice and non-incentivized economic beliefs
outstrips the correlation between vote choice and incentivized beliefs, suggesting that paying
survey particioants to be honest only results in an expensive version of cheap talk.
Given the concerns over the motives of survey respondents, scholars have used research
designs less subject to partisan cheerleading. For instance, Gerber and Huber (2010) find
that when party control of Congress switches, consumer behavior changes, and changes
along party lines, in anticipation of changes in the economy. After the Democrats took
over Congress in 2006, strong Democrats showed a 12.8% increase in holiday spending and
a 30.5% increase in vacation spending relative to strong Republicans. In an earlier study,
Gerber and Huber (2009) used data from county tax receipts to estimate that a county that
17
moves from 50% Democratic to 65% Democratic undergoes an increase in consumption .9%
higher following a Democratic presidential victory compared with a Republican presidential
victory. However, these empirical results have recently been challenged (McGrath, 2017),
and the relationship between partisanship and economic perceptions remains an important
area of scholarly inquiry.
Partisanship may spill over into other professional decisions as well. For example, Wintoki
and Xi (2017) find that mutual fund managers are more likely to invest in companies managed
by co-partisans. Although this behavior may be unconscious or due to selection on some
other dimension, it seems to conflict with the fiduciary duties of managers as partisan bias
does not improve fund performance and actually increases volatility. In medicine, Hersh and
Goldenberg (2016) find that Republican and Democratic physicians give different advice to
patients for politicized health issues such as abortion, but not on apolitical health topics. On
the patient side, Lerman, Sadin, and Trachtman (2017) leverage longitudinal data and find
that Republicans were less likely than Democrats to enroll in health insurance exchanges set
up by the Affordable Care Act, and Krupenkin (2016) shows that parents are more likely to
vaccinate their children when their party’s president is in the White House.
While we have focused here on the non-political consequences of affective polarization
and partisan animus, there is also the question of the political consequences of this phe-
nomenon. Interestingly, little has been written on this topic, as most studies have focused
on the more surprising apolitical ramifications discussed above. There are two important
counter-examples, however. First, there is evidence that affective polarization and out-party
animus fuels political activity: individuals’ dislike for the opposing party encourages them
to participate more in politics (Iyengar and Krupenkin, 2018). Second, another strand of
research by Hetherington and Rudolph (2015) shows that affective polarization undermines
trust on the part of the party that is out of power, and hence makes governing more complex.
This is only the beginning of research into the consequences of affective polarization.
More research is needed to understand how these factors play out in a variety of different
18
political contexts. For instance, do increases in affective polarization among the mass public
increase partisan discord among elites? More generally, does affective polarization threaten
to undermine the very mechanisms of electoral accountability through which elected officials
can be punished for misdeeds? Were Republicans in Alabama so hostile toward Democratic
Senate candidate Doug Jones that almost all of them voted for a candidate accused of
multiple sexual indiscretions? More research is needed to fully flesh out these behaviors.
Decreasing Affective Polarization
What, if anything, can be done to ameliorate affective polarization? While efforts here are at
best nascent, several approaches have shown promise. All of them work to reduce the biases
generated by partisanship’s division of the world into an in-group and an out-group. Hence,
some work has focused on making partisan identities less salient or making other identities
more salient.
First, scholars have shown that correcting misperceptions about party supporters reduces
animus toward the other side (Ahler and Sood, Forthcoming). The modal member of both
parties is a middle-aged, white, non-evangelical Christian, but this is not the image most
people carry around in their heads when they think about “Democrats” and “Republicans.”
Instead, most people think in terms of partisan stereotypes: Democrats are urban minorities
and young people, Republicans are older, wealthy, or evangelical Christians. Consequently,
when the typical American is asked about the composition of the parties, she tends to dra-
matically over-report the prevalence of partisan-stereotypical groups. While only about 11
percent of Democrats belong to a labor union, in a large national survey, the average Amer-
ican thought that 39 percent of Democrats were union members (44 percent of Republicans
had this perception along with 37 percent of Democrats). Likewise, while only 2.2 percent of
Republicans earn more than $250,000 per year, the average citizen thought that 38 percent of
Republicans earned that much. Looking across a range of party-stereotypical groups, Ahler
19
and Sood (Forthcoming) find that respondents over-estimate the prevalence of these groups
by 342 percent (5-6). These biases matter because people typically hold negative views to-
ward the other party’s stereotypical groups (see also Homola et al., 2016; Levendusky and
Malhotra, 2016b).4
If misperceptions about party composition increase partisan animus, possibly correcting
them could reduce affective polarization. Happily, this is exactly what scholars find. When
Ahler and Sood (Forthcoming) correct respondents misperceptions, respondents think the
other party is less extreme, and affective polarization decreases (i.e., they like the other
party more). In essence, people dislike the other party in part because they (inaccurately)
perceive it to be quite different from themselves and full of disliked groups. When this error
is corrected, and they realized the partisan out-group is more similar to them than they had
realized, animus lessens.5
A second approach tries to shift the salience of respondents’ partisan identities. Nor-
mally, when Democrats and Republicans think about one another, they perceive them as
members of a disliked partisan out-group. But they are also members of a common group:
they are all Americans. If Democrats and Republicans see one another as Americans, rather
than partisans, they move from out-group members to in-group ones, and hence group-based
partisan animus should fade. Using a set of survey experiments, as well as a natural exper-
iment stemming from the July Fourth holiday, Levendusky (2018) shows that emphasizing
American identity reduces animus toward the other party. For example, in his experimental
results, treated subjects (who had their American identity primed) were 25% less likely to
rate the other party at 0 degrees on a feeling thermometer scale, and 35% more likely to rate
4While Ahler and Sood (Forthcoming) do a commendable job of reviewing the consequences of suchmisperceptions, they have less to say about the causes of such erroneous beliefs. They offer some initialevidence that those who consume more political news hold more biased beliefs (see their Figure 2), suggestinga role for media coverage of the parties. More careful documentation of the sources of these stereotypes willbe an important step for future research.
5Similarly, Ahler (2014) shows that when people are explicitly told how moderate the average Americanis, respondents also become more moderate—correcting misperceptions can also mitigate ideological polar-ization as well. However, Levendusky and Malhotra (2016a) reach different conclusions using a differentoperationalization of the treatment.
20
the other party at 50 degrees or higher; there are similar effects for ratings of various traits
as well (see similar results by Carlin and Love (2018) on the capture of Osama bin Laden).
By showing what unites Democrats and Republicans, rather than emphasizing what divides
and differentiates them, partisan animus subsides.
More generally, the evidence suggests that making partisanship and politics less salient—
and emphasizing other factors—can potentially change behavior as well. For example, Ler-
man, Sadin, and Trachtman (2017) partnered with an outside organization (Enroll America)
to help uninsured individuals obtain health insurance through the federal marketplace. In-
dividuals who went to Enroll America’s website were directed either to the government-run
website (healthcare.gov) or to a private website (HealthSherpa.com). While the website
has no effect on the behavior of Democrats or Independents, it has an enormous effect on
Republicans: Republicans assigned to the private website are 20 percentage points more
likely to enroll in an insurance plan than Republicans assigned to the government website
(see their Figure 4 and the discussion on p. 764). Likely because of President Obama’s
association with the health insurance exchanges, partisan considerations shape Republicans
behavior here. But when they are shown a private website—which obscures the government’s
role—they become more willing to enroll. In an era of affective polarization, downplaying
politics can help to mitigate partisan divisions.
Both of these approaches represent important contributions to the literature, and high-
light important pathways to reducing partisan discord in the mass public. But there are two
important limitations to note. First, while both types of efforts appear to be effective, we
should not expect it to be easy to reduce partisan animus, even in the survey context, where
behavior tends to be quite malleable. While some strategies will work, many sensible strate-
gies will fail. For example, Levendusky (2017) uses a population-based survey experiment
to show that priming partisan ambivalence and using self-affirmation techniques—both of
which have been shown to reduce similar biases in other contexts—fail to reduce partisan
animus. It may be that in the contemporary political era, when partisanship is chronically
21
accessible, only quite strong primes are able to reduce affective polarization.
Further, it is unclear to what extent treatments that work in a survey experiment (or
other controlled settings) work in the messy reality of real-world politics. Even showing
that it is possible to reduce affective polarization and discord within the confines of a survey
experiment is an important contribution, but another important step for future research will
be to demonstrate that such effects can be generalized.
One potentially promising strand of research is to build off the insights of inter-group
contact theory (Pettigrew and Tropp, 2011) and examine whether constructive engagement
between Democrats and Republicans could potentially reduce partisan animus. This is also
related to a long tradition of work showing that diverse social networks—which expose
individuals to different political points of view—foster tolerance for opposing viewpoints,
which should also ameliorate affective polarization (Mutz, 2002). For example, several groups
have fostered small-scale discussions between ordinary Democrats and Republicans to try
and bridge the gap between the parties (Nelson, 2015). But there have been no systematic
evaluations of these efforts, and it seems questionable whether such efforts are scalable.
Open Questions and Concluding Thoughts
In this closing section we identify future research agendas and offer some thoughts on the
political significance of intensified partisan affect in the current era.
First, there has been little to no research identifying the mechanisms underlying affective
polarization. On the one hand, distaste for opposing partisans could be couched in raw,
reflexive emotion. This could result in extreme political responses based on blind hatred.
However, psychologists have long suggested that affect has informational content, so height-
ened affective polarization may also lead to more considered responses to both in and out
groups. For instance, the aversion to engage in economic transactions with opposing parti-
sans may stem not from a visceral emotional response, but because opponents are seen as
22
untrustworthy. This is akin to the distinction in the economics literature between animus
and statistical discrimination. Of course, existing research has noted that people’s stereo-
types of opposing partisans traits are inaccurate (both in terms of means and variances), so
distinguishing between these mechanisms seems important.
Second, the literature has yet to specify the conditions under which partisans are moti-
vated by either in-group favoritism or out-group animosity. Although social psychologists
studying group conflict have generally concluded that in-group affection is the dominant
force, the domain of politics might be distinctive. There is ample evidence that political
judgment is subject to a negativity bias (Soroka, 2014), implying that party polarization is
driven by out-group hostility. However, there is also evidence that in some situations par-
tisan bias is prompted more by in-group love (Lelkes and Westwood, 2017). One plausible
hypothesis is that the precise mix of in- and out-group sentiment will depend on individuals
prior information and how they update beliefs based on exposure to new information. For
instance, McConnell et al. (2018) found that consumers exhibited in-group favoritism toward
co-partisan sellers but not out-group animus toward opposite-party sellers. Perhaps this is
because their experimental participants had no prior relationship with the seller. On the
other hand, when people respond to a more well-known brand with which they have had a
previous relationship, they may be more likely to exhibit out-group animus in response to
partisan information and update negatively (as in Panagopoulos et al. (2016)). It is also
possible that the role of in groups and out groups in decision making is task dependent.
Social psychologists have suggested that contextual effects such as competition and threat
alter the degree to which people punish opponents or reward team members (Brewer, 1999).
Future research can more explicitly incorporate updating into experimental designs intended
to identify the relative contributions of in- and out-group sentiment to affective polarization.
As a third agenda item, we encourage researchers to explore the role of sorting as a
potential mediator of affective polarization. To the extent the alignment of ideology and
partisanship exacerbates polarization, sorted partisans should elicit a stronger outpouring
23
of either in-group favoritism or out-group animus. Yet we know of no work to date assesses
differences in partisans affect toward sorted and unsupported co-partisans or opponents.
Relatedly, scholars should examine the relative influence of social identities versus ideo-
logical sorting on affective polarization. Recent work indicates that while ideological polar-
ization, sorting, and affective polarization are correlated (Rogowski and Sutherland, 2016;
Bougher, 2017; Webster and Abramowitz, 2017), the relationship is rather weak, with sort-
ing accounting for only about 5 percent of the variance in affective polarization (Lelkes,
Forthcoming; Mason, 2018a). Furthermore, over the past 40 years, affective polarization in-
creased by about the same amount among those who held the most ideologically consistent
issue positions as those who held the least ideologically consistent issue positions (Lelkes,
Forthcoming). Further complicating any claim that affective polarization is a byproduct of
ideological sorting is the possibility that affective polarization may, in turn, increase sorting.
The most affectively polarized may be more likely to toe the party line and adopt party
policy positions.
Fourth, no research that we are aware of has identified ways in which affective polarization
drives both elite and mass ideological polarization. In terms of the former, we suspect that
affective polarization increases support for extremist politicians, or, at least, blinds partisans
to the ideological extremity of candidates from their party. In terms of the latter, we suspect
that affective polarization increases partisans’ willingness to conform to their party’s policy
positions. Hence, affective polarization may yield extreme politicians, who then send policy
cues to their base, exacerbating mass ideological polarization.
Finally, there has been little effort to draw out the connections between the American
politics literature on affective polarization and similar literatures in comparative politics
(though see Westwood et al. (2017) and Carlin and Love (2018)). Comparativists have
long recognized the importance of group identity to political behavior and attitudes, even
if they have not used the language of social identity theory or affective polarization. A
wide variety of findings in the literatures on ethnicity and distributive politics, as well as
24
on political violence, provide important theoretical and empirical insights for the study of
affective polarization. While we lack the space to review this literature here, more work is
needed to build bridges between Americanists and comparativists interested in these topics.
In conclusion, we note that increasing affective polarization can have grave ramifications,
especially during times of political turmoil. There is a broad similarity between the current
state of the Trump administration and the Watergate years; and yet, heightened polarization
has altered the political context in important ways. The Watergate scandal was brought to
light by investigative news reports that, over time, became widely accepted as credible and
eventually resulted in significant erosion of President Nixons approval among both Democrats
and Republicans alike (Lebo and Cassino, 2007). In contrast, the current pervasive drip of
scandal touching on the Trump administration has done little to weaken President Trump’s
popularity among Republicans who accuse the press and investigative bodies of partisan
bias (although see, Montagnes, Peskowitz, and McCrain, 2018). Partisanship appears to
now compromise the norms and standards we apply to our elected representatives, and even
leads partisans to call into question the legitimacy of election results, both of which threatens
the very foundations of representative democracy.
25
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